deep learning goodfellow

Caffe of Deep Learning (i) using C + + interface to extract features and classify them with SVM Reprint please dms contact Bo Master, do not reprint without consent. Recently because of the teacher's request to touch a little depth of learning and caffe things, one task is to use the ResNet network to extract the characteristics of the dataset and then use SVM t

Liu--unity Game Development Deep Learning Series Courses welfare big Send! Not only preferential, but also send unity the latest version of the necessary combat books! HI, all of you enthusiastic unity enthusiasts and students, "unity3d/2d game development from 0 to 1 (second edition)" book has been officially released. This book is based on the well-received first edition of the 2015, from the "heart" comb

Deep Learning Chinese Translation In the help of many netizens and proofreading, the draft slowly became the first draft. Although there are many problems, at least 90% of the content is readable and accurate. As far as possible, we kept the meaning of the original book Deep learning and kept the statement of the origi

Nowadays, AI is getting more and more attention, and this is largely attributed to the rapid development of deep learning. The successful cross-border between AI and different industries has a profound impact on traditional industries.Recently, I also began to keep in touch with deep learning, before I read a lot of ar

The following is only my personal knowledge, not to mention please PAT.(At present, I only see some deep learning review and Tom Mitchell's book "Machine Learning" in the Neural network chapter, the understanding is limited. Feel 3\4 speak generally, reluctantly a look. The fifth chapter is purely to make notes, really bad expression, do not understand or look at

Deep Learning Library packages Theano, Lasagne, and TensorFlow support GPU installation in Ubuntu With the popularity of deep learning, more and more people begin to use deep learning to train their own models. GPU training is muc

First spit groove, deep learning development speed is really fast, deep learning framework is gradually iterative, it is really hard for me to engage in deep learning programmer. I began three years ago to learn

weight ratio, if the 10^-3 around is better, if too small, the learning speed will be relatively slow, too big words will be unstable.Initialization weights: at the beginning of the random initialization weightsThe initialization method mentioned here will not be particularly clear or not written. However, it is said that for shallow network simpler initialization method, the network can also work normally, but for

Deep learning articles and code collections for text categorizationOriginal: franklearningmachine Machine Learning blog 4 days ago [1] convolutional neural Networks for sentence classificationYoon KimNew York UniversityEMNLP 2014http://www.aclweb.org/anthology/D14-1181This article mainly uses CNN to classify sentences based on pre-trained word vectors. The auth

Source: Michael Nielsen's "Neural Network and Deep learning", click the end of "read the original" To view the original English.This section translator: Hit Scir undergraduate Wang YuxuanDisclaimer: If you want to reprint please contact [email protected], without authorization not reproduced. Using neural networks to recognize handwritten numbers How the inverse propagation algorithm wor

Python to do deep learning caffe design CombatEssay background: In a lot of times, many of the early friends will ask me: I am from other languages transferred to the development of the program, there are some basic information to learn from us, your frame feel too big, I hope to have a gradual tutorial or video to learn just fine. For learning difficulties do no

Preface: Recently, I intend to learn some theoretical knowledge of deep learing in a slightly systematic way, and intend to use Andrew Ng's Web tutorial Ufldl Tutorial, which is said to be easy to read and not too long. But before this, or review the basic knowledge of machine learning, see Web page: http://openclassroom.stanford.edu/MainFolder/CoursePage.php?course=DeepLearning. The content is actually ver

companies want to go to the company to brush the work card, but here we do not need it, using face recognition, see what I can do. When I come close, it will recognize my face and then say "Welcome" (Andrew NG), I can pass without a work-cards. Let's take a look at another situation, next to Lin Yuanqing, IDL (Baidu Deep Learning Laboratory) Director, he led the development of the face recognition system,

The key of AI is machine learning, machine learning breakthrough is deep learning, artificial neural network.In 1956, in the Dartmouth Conference (Dartmouth conferences), computer scientists first introduced the term "AI", the AI was born, and in subsequent days AI became the "fantasy object" of the lab. Decades later,

the node matrix or the number of input Samples # Fourth parameter: Fill method, ' same ' means full 0 padding, ' VALID ' means no padding TensorFlow to realize the forward propagation of the average pool layer Pool = Tf.nn.avg_pool (actived_conv,ksize[1,3,3,1],strides=[1,2,2,1],padding= ' same ') # first parameter: Current layer node Matrix # The second parameter: the size of the filter # gives a one-dimensional array of length 4, but the first and last of the array must be 1

constitute the model family.Generalized Lagrangian functions:ADMM algorithm iterative update process:(\beta_{l}=\frac{\alpha_{l}}{\rho_{l}},a=pf\) (known), can be\ (S (\cdot) \) is a nonlinear shrinkage function. \ (S (\cdot) \) is usually a smooth function.Network structure:including the reconstruction Layer \ (x^{(n)}\), convolutional layer \ (c^{(n)}=d_{l}x^{(n)}\), nonlinear transformation layer \ (z^{(n)}\), multiply sub-update layer \ (m^{(n)}\), where the nonlinear transformation functio

Visual Tracking Method: The DLT (deep learning tracker) is really a fire, it should be able to represent the 2013 tracking field of State-of-art. Recently, it has been carefully studied, in accordance with the framework, core ideas, the prospect of "deep analysis." Frame The entire algorithm is still in the mainstream pf (particle filter) probabilistic framework

From self learning to deep network In the previous section, we used the self encoder to learn the characteristics of input to the Softmax or logistic regression classifier. These features are only learned using data that is not annotated. In this section, we describe how to fine-tune these features using the annotated data for further refinement. If you have a large number of tagged data, you can significan

Deep Learning Notes (i): Logistic classificationDeep learning Notes (ii): Simple neural network, back propagation algorithm and implementationDeep Learning Notes (iii): activating functions and loss functionsDeep Learning Notes: A summary of optimization methodsDeep

Part III: Deep Learning vs SLAMSLAM group discussion is really fun. Before we go into the important "deep learning vs slam" "discussion, I should say that every seminar contributor agrees: Semantics are necessary to build a larger and better SLAM system. There are lots of interesting little conversations about the futu